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1. Mixture model-based classification
by McNicholas, Paul D., author
2016, 1, ISBN 1482225662, xxiv, 212 pages
Mixture Model-Based Classification is the first monograph devoted to mixture model-based approaches to clustering and classification. This is both a book for... 
Hierarchical clustering (Cluster analysis) | Discriminant analysis | Multiple comparisons (Statistics) | Classification | Mixture distributions (Probability theory) | Mathematics | Methods | Statistical Theory & Methods | Bioinformatics | Psychological Methods & Statistics
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2. Multilevel models
: applications using SAS
by Wang, Jichuan and Xie, Haiyi and Fischer, James H
2012, ISBN 9783110267594, ix, 264 pages
Multilevel models (Statistics) | Social sciences | Modèles mathématiques | Mathematical models | Research | Sciences sociales | Recherche | Modèles multiniveaux (Statistique)
Book
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3. Full Text Regression and model-building in conservation biology, biogeography and ecology: The distinction between – and reconciliation of – ‘predictive’ and ‘explanatory’ models
by Mac Nally, Ralph
Biodiversity and Conservation, ISSN 0960-3115, 5/2000, Volume 9, Issue 5, pp. 655 - 671
In many large-scale conservation or ecological problems where experiments are intractable or unethical, regression methods are used to attempt to gauge the... 
Life Sciences | hierarchical partitioning | inference | criteria | model selection | multiple regression | Evolutionary Biology | Tree Biology | Plant Sciences | model artefacts | Inference | Criteria | Model selection | Model artefacts | Hierarchical partitioning | Multiple regression | LINEAR-REGRESSION | LANDSCAPE | MULTIPLE-REGRESSION | COASTAL SOUTHERN CALIFORNIA | ABUNDANCE | SUBSET REGRESSION | ENVIRONMENTAL SCIENCES | HABITAT | SPECIES RICHNESS | ECOLOGY | VARIABLES | SELECTION | BIODIVERSITY CONSERVATION | Geography | Modelling (-General-) | Regression Analysis | Modelling (-Specific Names-II) | Ecology | Modelling (- Specific Names-I) | Modelling (-Specific Names-I) | Studies | Regression analysis
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4. Multilevel modeling
by Luke, Douglas A
2004, ISBN 0761928790, 88
Multivariate analysis | Multilevel models (Statistics)
Book
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5. Full Text How to model species responses along ecological gradients – Huisman–Olff–Fresco models revisited
by Florian Jansen and Jari Oksanen
Journal of Vegetation Science, ISSN 1100-9233, 11/2013, Volume 24, Issue 6, pp. 1108 - 1117
Questions: In species response modelling, can a hierarchical logistic regression framework compete against GAM in terms of statistical inference? Are bimodal... 
Datasets | Ecological modeling | Statistical models | Vegetation | Multilevel models | Plants | Species | Parametric models | Modeling | Realized niche | Bioindication | Hierarchical modelling | Logistic regression | Species turnover | Species optimum | Environmental gradient | Agricultural land
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6. Full Text Growth Modeling Using Random Coefficient Models: Model Building, Testing, and Illustrations
by Bliese, Paul D and Ployhart, Robert E
2011, ISBN 9781848606999, Volume 5, Issue 4, 26
For more than 40 years, SAGE has been one of the leading international publishers of works on quantitative research methods in the social sciences. This new... 
INTRAINDIVIDUAL CHANGES | CRITERIA | INTERINDIVIDUAL DIFFERENCES | MANAGEMENT | INDIVIDUAL CHANGE | PERFORMANCE | HIERARCHICAL LINEAR-MODELS | TIME | Regression analysis | Research | Random variables | Growth models | Freeware | Construction | Foundations | Regression | Mathematical models | Coefficients | Readers | Guidelines
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7. Mixture model-based classification
by McNicholas, Paul D
2016, ISBN 1482225662
Hierarchical clustering (Cluster analysis) | Discriminant analysis | Multiple comparisons (Statistics) | Classification | Mixture distributions (Probability theory) | Mathematics | Methods
Web Resource
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8. Full Text Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data
by DiRenzo, Graziella V and Che‐Castaldo, Christian and Saunders, Sarah P and Campbell Grant, Evan H and Zipkin, Elise F
Ecology and Evolution, ISSN 2045-7758, 01/2019, Volume 9, Issue 2, pp. 899 - 909
Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires... 
generalized | occupancy model | Bayesian | emerging infectious diseases | host–pathogen interaction | hierarchical models | mark–recapture models | mixture model | multistate models | disease ecology | Dail–Madsen model | generalized N-mixture model | host-pathogen interaction | PATHOGEN | STATE | SITE OCCUPANCY MODELS | DIAGNOSTIC-TESTS | PREVALENCE | CAPTURE-RECAPTURE ANALYSIS | Dail-Madsen model | EVOLUTIONARY BIOLOGY | mark-recapture models | WILDLIFE | ECOLOGY | IMPERFECT | POPULATION-DYNAMICS | MALARIA INFECTIONS | Parameter estimation | Populations | Theory | Population number | Infections | Statistical methods | Probabilistic models | Biodiversity | Reptiles & amphibians | Ecologists | Wildlife | Dynamics | Population | Mathematical models | Arachnids | Pathogens | Statistical analysis | Probability | Birds | Ecology | Estimates | Disease control | Manuscripts | Biological diversity | Population (statistical) | Infectious diseases | Disease transmission | State space models | Immigration | Error detection | Wildlife management
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9. Full Text runjags: An R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS
by Denwood, Matthew J
Journal of Statistical Software, ISSN 1548-7660, 07/2016, Volume 71, Issue 9, pp. 1 - 25
The runjags package provides a set of interface functions to facilitate running Markov chain Monte Carlo models in JAGS from within R. Automated calculation of... 
BUGS | MCMC | JAGS | Graphical models | Interface utilities | Bayesian | HIERARCHICAL-MODELS | STATISTICS & PROBABILITY | CHAIN MONTE-CARLO | interface utilities | R | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | graphical models | CONVERGENCE | EXAMPLE | VARIANCE
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10. Full Text Model selection and assessment for multi-species occupancy models
by Kristin M. Broms and Mevin B. Hooten and Ryan M. Fitzpatrick
Ecology, ISSN 0012-9658, 7/2016, Volume 97, Issue 7, pp. 1759 - 1770
While multi-species occupancy models (MSOMs) are emerging as a popular method for analyzing biodiversity data, formal checking and validation approaches for... 
Bayesian hierarchical models | biodiversity | species distribution maps | cross‐validation | plains fish | South Platte River Basin | REGRESSION-MODELS | DETECTABILITY | cross-validation | PENALIZED LIKELIHOOD | INFERENCE | HILL NUMBERS | COMMUNITY | SPECIES RICHNESS | ECOLOGY | ABUNDANCE MODELS | IMPERFECT DETECTION | Animals | Fishes - classification | Colorado | Ecosystem | Bayes Theorem | Conservation of Natural Resources | Models, Statistical | Biodiversity | Fishes - physiology | Fish populations | Observations | Stock assessment (Wildlife management) | Methods
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11. Full Text Galactic stellar haloes in the CDM model
by Cooper, A. P and Cole, S and Frenk, C. S and White, S. D. M and Helly, J and Benson, A. J and De Lucia, G and Helmi, A and Jenkins, A and Navarro, J. F and Springel, V and Wang, J
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 2010, Volume 406, Issue 2, pp. 744 - 766
We present six simulations of galactic stellar haloes formed by the tidal disruption of accreted dwarf galaxies in a fully cosmological setting. Our model is... 
Galaxy: halo | Galaxies: haloes | Galaxies: formation | Galaxies: structure | Galaxies: dwarf | Methods: numerical | COLD DARK-MATTER | MILKY-WAY SATELLITES | GLOBULAR-CLUSTER SYSTEM | METAL-POOR STARS | SURVEY COMMISSIONING DATA | methods: numerical | N-BODY SIMULATIONS | galaxies: dwarf | galaxies: formation | galaxies: structure | RR LYRAE STARS | DIGITAL SKY SURVEY | ASTRONOMY & ASTROPHYSICS | DWARF SPHEROIDAL GALAXIES | HIERARCHICAL GALAXY FORMATION | galaxies: haloes | Milky Way | Stars & galaxies | Models
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12. Full Text A Hierarchical Model for Spatial Capture-Recapture Data
by J. Andrew Royle and Kevin V. Young
Ecology, ISSN 0012-9658, 8/2008, Volume 89, Issue 8, pp. 2281 - 2289
Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed... 
Wildlife ecology | Density estimation | Horned lizards | Ecological modeling | Animals | Multilevel models | Emigration | Population estimates | Population size | Modeling | distance sampling | spatial point process | abundance estimation | data augmentation | Phrynosoma mcallii | trapping grid | hierarchical modeling | animal movement models | Bayesian analysis | density estimation | trapping web | Animal movement models | Trapping grid | Distance sampling | Hierarchical modeling | Spatial point process | Data augmentation | Abundance estimation | Trapping web | MIXTURE-MODELS | DETECTION PROBABILITY | POPULATION-SIZE | TAILED HORNED LIZARD | COUNTS | DENSITY ESTIMATORS | ROBUST DESIGN | WEB | ECOLOGY | TEMPORARY EMIGRATION | Lizards - physiology | Demography | Models, Biological | Computer Simulation | Ecosystem | Bayes Theorem | Monte Carlo Method | Research Design | Bayesian statistical decision theory | Measurement | Evaluation | Horned toads | Animal locomotion | Distribution | Environmental aspects | Methods | Population density
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13. Full Text The Kuramoto model in complex networks
by Rodrigues, Francisco A and Peron, Thomas K. DM and Ji, Peng and Kurths, Jürgen
Physics Reports, ISSN 0370-1573, 01/2016, Volume 610, pp. 1 - 98
Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and... 
GLOBALLY COUPLED OSCILLATORS | COMMUNITY STRUCTURE | CHIMERA STATES | PHYSICS, MULTIDISCIPLINARY | SCALE-FREE NETWORKS | PHASE OSCILLATORS | ARBITRARY DEGREE DISTRIBUTIONS | LIMIT-CYCLE OSCILLATORS | SYNCHRONIZATION TRANSITION | HIERARCHICAL ORGANIZATION | EXPLOSIVE SYNCHRONIZATION
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